Decreased urine output is associated with increased in-hospital mortality from sepsis-associated acute respiratory distress syndrome
1Department of Geriatrics and Special Service Medicine, First Affiliated Hospital of Army Medical University (Southwest Hospital), 400038 Chongqing, China
2Department of Critical Care Medicine, the Second Affiliated Hospital of Chongqing Medical University, 400010 Chongqing, China
3Department of Cardiology, the Second Affiliated Hospital, Chongqing Medical University, 400010 Chongqing, China
4Precision Medicine Center, the Second Affiliated Hospital of Chongqing Medical University, 400010 Chongqing, China
DOI: 10.22514/sv.2023.028 Vol.19,Issue 3,May 2023 pp.112-120
Submitted: 31 August 2022 Accepted: 18 October 2022
Published: 08 May 2023
*Corresponding Author(s): Yake Lou E-mail: firstname.lastname@example.org
*Corresponding Author(s): Tianyang Hu E-mail: email@example.com
† These authors contributed equally.
The relationship between urine output (UO) and in-hospital mortality in patients with sepsis-associated acute respiratory distress syndrome (ARDS) has not been elucidated. The demographic and clinical characteristics of patients from the intensive care unit with sepsis-associated ARDS in the Medical Information Mart for Intensive Care-IV database were collected, and binomial logistic regression was performed to determine whether UO was an independent risk factor for in-hospital death. Using the Logistic Organ Dysfunction System (LODS) and Sequential Organ Failure Assessment (SOFA) as a reference, receiver operating characteristic (ROC) curves were drawn to analyze the efficacy of UO in predicting in-hospital mortality, and the Kaplan-Meier curve was drawn with the optimal cut-off value of the ROC curve. Decision curve analysis (DCA) was performed to assess the clinical net benefit of UO in predicting in-hospital mortality. UO was an independent risk factor for in-hospital mortality in patients with sepsis-associated ARDS. The area under the ROC (AUC) for UO in predicting in-hospital mortality was 0.712, which was comparable to LODS and SOFA. The patients were grouped by the optimal UO cut-off value (1515 mL/day) identified by the ROC curve. The results showed that the median in-hospital survival time for the low-UO group was 20.565 days, and that of the high-UO group was 84.670 days. The risk of in-hospital death of the low-UO group was 3.0792 times that of the high-UO group. DCA showed that when using UO to predict in-hospital mortality, the clinical net benefit was higher than LODS or SOFA at almost all available threshold probabilities, particularly when the threshold probability was between 0.2 and 0.4. As a result, UO showed moderate efficacy in predicting in-hospital mortality, and when used to predict the in-hospital mortality of patients with sepsis-related ARDS, its clinical net benefit was higher than that of LODS or SOFA.
Urine output; Sepsis; Acute respiratory distress syndrome; In-hospital mortality; MIMIC-IV
Fuli Cao,Yiting Liu,Yake Lou,Tianyang Hu. Decreased urine output is associated with increased in-hospital mortality from sepsis-associated acute respiratory distress syndrome. Signa Vitae. 2023. 19(3);112-120.
 Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016; 315: 801–810.
 ARDS Definition Task Force, Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, Fan E, et al. Acute respiratory distress syndrome: the Berlin Definition. JAMA. 2012; 307: 2526–2533.
 Guillen-Guio B, Lorenzo-Salazar JM, Ma S, Hou P, Hernandez-Beeftink T, Corrales A, et al. Sepsis-associated acute respiratory distress syndrome in individuals of European ancestry: a genome-wide association study. The Lancet Respiratory Medicine. 2020; 8: 258–266.
 Mikkelsen ME, Shah CV, Meyer NJ, Gaieski DF, Lyon S, Miltiades AN, et al. The epidemiology of acute respiratory distress syndrome in patients presenting to the emergency department with severe sepsis. Shock. 2013; 40: 375–381.
 Sevransky JE, Martin GS, Shanholtz C, Mendez-Tellez PA, Pronovost P, Brower R, et al. Mortality in sepsis versus non-sepsis induced acute lung injury. Critical Care. 2009; 13: R150.
 Li X, Shen H, Zhou T, Cao X, Chen Y, Liang Y, et al. Does an increase in serum FGF21 level predict 28-day mortality of critical patients with sepsis and ARDS? Respiratory Research. 2021; 22: 182.
 Zhang Z, Xu X, Ni H, Deng H. Urine output on ICU entry is associated with hospital mortality in unselected critically ill patients. Journal of Nephrology. 2014; 27: 65–71.
 Heffernan AJ, Judge S, Petrie SM, Godahewa R, Bergmeir C, Pilcher D, et al. Association between urine output and mortality in critically Ill patients: a machine learning approach. Critical Care Medicine. 2022; 50: e263–e271.
 Hu T, Qiao Z, Mei Y. Urine output is associated with in-hospital mortality in intensive care patients with septic shock: a propensity score matching analysis. Frontiers in Medicine. 2021; 8: 737654.
 Hsiao C, Chang C, Fan P, Ho H, Jenq C, Kao K, et al. Prognosis of patients with acute respiratory distress syndrome on extracorporeal membrane oxygenation: the impact of urine output on mortality. The Annals of Thoracic Surgery. 2014; 97: 1939–1944.
 Shen Y, Cai G, Chen S, Hu C, Yan J. Fluid intake-related association between urine output and mortality in acute respiratory distress syndrome. Respiratory Research. 2020; 21: 24.
 Johnson AEW, Pollard TJ, Shen L, Lehman LH, Feng M, Ghassemi M, et al. MIMIC-III, a freely accessible critical care database. Scientific Data. 2016; 3: 160035.
 Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases. 1987; 40: 373–383.
 DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988; 44: 837–845.
 Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Medical Decision Making. 2006; 26: 565–574.
 Wang L, Zhang Z, Hu T. Effectiveness of LODS, OASIS, and SAPS II to predict in-hospital mortality for intensive care patients with ST elevation myocardial infarction. Scientific Reports. 2021; 11: 23887.
 Rosenberg AL. Recent innovations in intensive care unit risk-prediction models. Current Opinion in Critical Care. 2002; 8: 321–330.
 Legrand M, Payen D. Understanding urine output in critically ill patients. Annals of Intensive Care. 2011; 1: 13.
 Wilson WC, Aronson S. Oliguria. A sign of renal success or impending renal failure? Anesthesiology Clinics of North America. 2001; 19: 841–883.
 Sibbald WJ, Short AK, Warshawski FJ, Cunningham DG, Cheung H. Thermal dye measurements of extravascular lung water in critically ill patients. Intravascular Starling forces and extravascular lung water in the adult respiratory distress syndrome. Chest. 1985; 87: 585–592.
 Peake SL, Delaney A, Bailey M, Bellomo R, Cameron PA, Cooper DJ, et al. Goal-directed resuscitation for patients with early septic shock. The New England Journal of Medicine. 2014; 371: 1496–1506.
Vol., Issue , Invalid dateTable of contents
Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,200 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.
Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.
Chemical Abstracts Service Source Index The CAS Source Index (CASSI) Search Tool is an online resource that can quickly identify or confirm journal titles and abbreviations for publications indexed by CAS since 1907, including serial and non-serial scientific and technical publications.
Index Copernicus The Index Copernicus International (ICI) Journals database’s is an international indexation database of scientific journals. It covered international scientific journals which divided into general information, contents of individual issues, detailed bibliography (references) sections for every publication, as well as full texts of publications in the form of attached files (optional). For now, there are more than 58,000 scientific journals registered at ICI.
Geneva Foundation for Medical Education and Research The Geneva Foundation for Medical Education and Research (GFMER) is a non-profit organization established in 2002 and it works in close collaboration with the World Health Organization (WHO). The overall objectives of the Foundation are to promote and develop health education and research programs.
Scopus: CiteScore 0.5(2021) Scopus is Elsevier's abstract and citation database launched in 2004. Scopus covers nearly 36,377 titles (22,794 active titles and 13,583 Inactive titles) from approximately 11,678 publishers, of which 34,346 are peer-reviewed journals in top-level subject fields: life sciences, social sciences, physical sciences and health sciences.
Embase Embase (often styled EMBASE for Excerpta Medica dataBASE), produced by Elsevier, is a biomedical and pharmacological database of published literature designed to support information managers and pharmacovigilance in complying with the regulatory requirements of a licensed drug.